code: def create_deployment(
      self, name, model_uri, flavor=None, config=None, endpoint=None
  ):
      if config and config.get("raiseError") == "True":
          raise RuntimeError("Error requested")
      return {"name": f_deployment_name, "flavor": flavor}
  
file_path: mlflow/tests/resources/mlflow-test-plugin/mlflow_test_plugin/fake_deployment_plugin.py
imports: import os
  from mlflow.deployments import BaseDeploymentClient, PredictionsResponse
label_desc: Use image node_id 1 for calling the PluginDeploymentClient obj's underlying member method code with example usage: obj.create_deployment(name, model_uri, flavor, config, endpoint) and returns: dict